cb.reset.parameters

a list where each element corresponds to a parameter that needs to be reset.
Each element's value must be either a vector of values of length <code>nrounds</code> 
to be set at each iteration, 
or a function of two parameters <code>learning_rates(iteration, nrounds)</code> 
which returns a new parameter value by using the current iteration number 
and the total number of boosting rounds.

new_params


Callback closure for restetting the booster's parameters at each iteration.


Extreme Gradient Boosting, which is an efficient implementation
of the gradient boosting framework from Chen & Guestrin (2016) <doi:10.1145/2939672.2939785>.
This package is its R interface. The package includes efficient linear
model solver and tree learning algorithms. The package can automatically
do parallel computation on a single machine which could be more than 10
times faster than existing gradient boosting packages. It supports
various objective functions, including regression, classification and ranking.
The package is made to be extensible, so that users are also allowed to define
their own objectives easily.

cb.reset.parameters: Callback closure for restetting the booster's parameters at each iteration.

Description

Usage

Arguments

Details

See Also